Forward Deployed Engineer (FDE) - AI Infra - SF

Fdetimes; San Francisco (CA); Hybrid; USD 180,000 - 280,000; Full time

Benefits offered by this job

Relocation assistance

Travel up to 50%

Job summary

OpenAI Forward Deployed Engineers lead complex deployments of frontier models in production, embedding with customers where performance and urgency matter. You will write and debug software, run experiments against real workloads and hardware, and ship tools across engagements.

This role is based in San Francisco with a hybrid model (3 days in the office) and relocation assistance; travel up to 50% is required.

Qualifications

• 5+ years of engineering or technical deployment with customer-facing work.
• Experience delivering complex systems in fast-moving or ambiguous environments.
• Write and debug production-grade software across code, integrations and runtime.
• Experience with systems powered by LLMs or generative models.
• Ability to translate ambiguous problems into clear evaluations and experiments.
• Excellent communication with engineers, product teams, and customer stakeholders.

Responsibilities

• Own technical delivery for semiconductor and AI-infra workstreams from scoping to deployment.
• Work with customer engineers to define workloads, baselines and success criteria.
• Sequence delivery, identify dependencies and balance scope, speed and quality.
• Build and debug production-quality software, harnesses and integrations.
• Design reproducible experiments, evaluations and benchmarks to test approaches.
• Investigate model behavior with researchers and contribute data and experiments.
• Contribute to core product development and tooling improvements.
• Lead technical discussions and align across customers, Product and Research teams.
• Turn successful approaches into reusable software, tools and playbooks.

Skills

Customer-facing delivery

Production-grade software

LLMs/generative models

Strong communication

Problem solving under pressure

End-to-end deployment

Cross-team collaboration

Hands-on ML experimentation

Job description

About the team

OpenAI's Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development.

About the role

Forward Deployed Engineers lead complex deployments of frontier models in production. You will embed with customers where model performance matters, delivery is urgent, and ambiguity is the default. You will use this to map their problems, structure delivery, and ship fast.

As a Forward Deployed Engineer for AI Infra, you will work directly with customer engineers, researchers and product engineers on optimization problems across semiconductors and AI infrastructure. You will write and debug software, run experiments against real workloads and hardware, and improve the tools and product used across engagements.

You will help define the problem and success criteria, build the software needed to test an approach, and stay with the work through validation and deployment. Work may include inference performance and chip-design optimization. Success means producing results that stand up to correctness and performance checks, and contributing improvements that other engagements can use.

Success in this role means owning the delivery state across workstreams. You will hold the bar on quality and pace and help OpenAI learn through execution.

This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required.

In this role, you will

• Own technical delivery for agreed semiconductor and AI-infrastructure workstreams, from initial scoping and prototypes through validation, production deployment and adoption.
• Work closely with customer engineers to understand their workflows and constraints, define workloads, baselines and success criteria, and help what you build become part of how they work.
• Scope and sequence delivery, identify dependencies and blockers early, and make practical trade-offs between scope, speed and quality as the work develops.
• Personally build and debug production-quality software, including harnesses, integrations and product features that apply frontier models to problems in chip design, verification, inference and performance engineering.
• Design reproducible experiments, evaluations, graders and benchmarks to test approaches, validate correctness and performance, and establish whether improvements hold up in real engineering environments.
• Investigate model behavior and failure modes alongside researchers, contributing evaluation or training data and targeted experiments where they can improve the underlying capability.
• Contribute directly to core product development, working with product engineers to resolve tooling gaps, ship useful improvements and bring field learning into product decisions.
• Lead technical discussions and maintain alignment across customer, Product and Research teams. Build the domain and product fluency to explain capabilities, limitations and results, and keep ownership, risks and next steps clear.
• Turn successful approaches into reusable software, tools and playbooks, reducing the effort needed for future engagements and helping customer teams operate what has been built.

You might thrive in this role if you

• Bring 5+ years of engineering or technical deployment experience that includes customer-facing work
• Have scoped and delivered complex systems in fast-moving or ambiguous environments
• Write and review production-grade software, and debug unfamiliar systems across code, integrations and runtime behavior.
• Have built or deployed systems powered by LLMs or generative models and understand how model behaviour affects product experience
• Simplify complexity and make fast, sound decisions under pressure
• Communicate clearly with engineers, product teams, and customer stakeholders
• Spot risks early and adjust without slowing down
• Model calm and judgment when the stakes are high
• Have a strong product sense and have contributed towards productizing efforts
• Have hands-on experience with applied machine learning, model evaluation, data quality, experimentation, or model-behavior analysis
• Can turn an ambiguous technical problem into a clear evaluation, a credible baseline, and a reproducible experiment
• Are comfortable learning unfamiliar technical domains and working closely with researchers, product engineers and customer engineers. Experience in semiconductor development, data-center systems or inference engineering is helpful.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

For additional information, please see OpenAI’s Affliative Action and Equal Employment Opportunity Policy Statement.

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.

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